A fundamental challenge in many areas of science is to understand how coordinated network activity arises from the network connectivity and the intrinsic properties of oscillating units. This challenge is of importance in Neuroscience. Neuronal networks that produce r hythmic motor behaviors, such as locomotion, provide important model systems to address this challenge. A particularly good model system for this purpose is the neural circuit underlying the coordinated rhythmic limb movements in the crayfish swimmeret system.

Limbs of crayfish, called swimmerets, move rhythmically in a metachronal wave that progresses from the back to front of the animal during forward swimming. The swimmerets paddle with the same period, but neighboring swimmerets maintain phase-lags of ~25% of the period. This coordination of limb movements is maintained over a wide range of frequency. In this talk, I will discuss recent experimental and theoretical work that provides insight into the mechanisms underlying this robustly stable phase-locked rhythm.